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相关论文: Emergent Persuasion: Will LLMs Persuade Without Be…

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Large language models (LLMs) are susceptible to persuasion, which can pose risks when models are faced with an adversarial interlocutor. We take a first step towards defending models against persuasion while also arguing that defense…

计算与语言 · 计算机科学 2025-02-11 Elias Stengel-Eskin , Peter Hase , Mohit Bansal

Despite recent advances, Large Language Models remain vulnerable to jailbreak attacks that bypass alignment safeguards and elicit harmful outputs. While prior research has proposed various attack strategies differing in human readability…

计算与语言 · 计算机科学 2025-10-28 Havva Alizadeh Noughabi , Julien Serbanescu , Fattane Zarrinkalam , Ali Dehghantanha

This is the first of a series of short reports that seek to help business, education, and policy leaders understand the technical details of working with AI through rigorous testing. In this report, we demonstrate two things: - There is no…

计算与语言 · 计算机科学 2025-03-10 Lennart Meincke , Ethan Mollick , Lilach Mollick , Dan Shapiro

Persuasion, a fundamental social capability for humans, remains a challenge for AI systems such as large language models (LLMs). Current studies often overlook the strategic use of information asymmetry in message design or rely on strong…

计算与语言 · 计算机科学 2025-10-17 Buwei He , Yang Liu , Zhaowei Zhang , Zixia Jia , Huijia Wu , Zhaofeng He , Zilong Zheng , Yipeng Kang

Recent research on large language models (LLMs) has demonstrated their ability to understand and employ deceptive behavior, even without explicit prompting. However, such behavior has only been observed in rare, specialized cases and has…

计算与语言 · 计算机科学 2025-06-24 Laurène Vaugrante , Francesca Carlon , Maluna Menke , Thilo Hagendorff

While Large Language Models (LLMs) are being quickly adapted to many domains, including healthcare, their strengths and pitfalls remain under-explored. In our study, we examine the effects of prompt engineering to guide Large Language…

计算与语言 · 计算机科学 2024-09-04 Daniil Filienko , Yinzhou Wang , Caroline El Jazmi , Serena Xie , Trevor Cohen , Martine De Cock , Weichao Yuwen

Large Language Models (LLMs) are increasingly regarded as having the potential to generate persuasive content at scale. While previous studies have focused on the risks associated with LLM-generated misinformation, the role of LLMs in…

计算机与社会 · 计算机科学 2026-04-06 John Caffier , Olga Stavrova , Bennett Kleinberg

Large language models (LLMs) have significantly advanced dialogue systems and role-playing agents through their ability to generate human-like text. While prior studies have shown that LLMs can exhibit distinct and consistent personalities,…

计算与语言 · 计算机科学 2025-02-18 Shu Yang , Shenzhe Zhu , Liang Liu , Lijie Hu , Mengdi Li , Di Wang

Generative AI, including large language models (LLMs) have the potential -- and already are being used -- to increase the speed, scale, and types of unsafe conversations online. LLMs lower the barrier for entry for bad actors to create…

人机交互 · 计算机科学 2025-07-31 Owen Hoffman , Kangze Peng , Zehua You , Sajid Kamal , Sukrit Venkatagiri

When using large language models (LLMs) in high-stakes applications, we need to know when we can trust their predictions. Some works argue that prompting high-performance LLMs is sufficient to produce calibrated uncertainties, while others…

Modern language models are trained on large amounts of data. These data inevitably include controversial and stereotypical content, which contains all sorts of biases related to gender, origin, age, etc. As a result, the models express…

计算与语言 · 计算机科学 2025-09-03 Aleksandra Sorokovikova , Pavel Chizhov , Iuliia Eremenko , Ivan P. Yamshchikov

Psychological consultation is essential for improving mental health and well-being, yet challenges such as the shortage of qualified professionals and scalability issues limit its accessibility. To address these challenges, we explore the…

计算与语言 · 计算机科学 2024-08-30 Rafael Souza , Jia-Hao Lim , Alexander Davis

Large language models are highly sensitive to prompts, but this sensitivity is usually studied through task-relevant instructions, demonstrations, or reasoning cues. In this paper, we study a different form of prompt sensitivity: whether…

计算与语言 · 计算机科学 2026-05-29 Pawel Batorski , Abtin Pourhadi , Jerzy Sarosiek , Przemyslaw Spurek , Paul Swoboda

Large Language Models (LLMs) are increasingly being utilized by both candidates and employers in the recruitment context. However, with this comes numerous ethical concerns, particularly related to the lack of transparency in these…

计算与语言 · 计算机科学 2024-02-16 Airlie Hilliard , Cristian Munoz , Zekun Wu , Adriano Soares Koshiyama

Persona prompting is increasingly used in large language models (LLMs) to simulate views of various sociodemographic groups. However, how a persona prompt is formulated can significantly affect outcomes, raising concerns about the fidelity…

计算与语言 · 计算机科学 2025-10-06 Marlene Lutz , Indira Sen , Georg Ahnert , Elisa Rogers , Markus Strohmaier

Large language models (LLMs) are known to produce varying responses depending on prompt phrasing, indicating that subtle guidance in phrasing can steer their answers. However, the impact of this framing bias on LLM-based evaluation, where…

计算与语言 · 计算机科学 2026-01-21 Yerin Hwang , Dongryeol Lee , Taegwan Kang , Minwoo Lee , Kyomin Jung

We are exposed to much information trying to influence us, such as teaser messages, debates, politically framed news, and propaganda - all of which use persuasive language. With the recent interest in Large Language Models (LLMs), we study…

计算与语言 · 计算机科学 2025-02-24 Amalie Brogaard Pauli , Isabelle Augenstein , Ira Assent

Large language models (LLMs) can reproduce a wide variety of rhetorical styles and generate text that expresses a broad spectrum of sentiments. This capacity, now available at low cost, makes them powerful tools for manipulation and…

社会与信息网络 · 计算机科学 2024-05-08 Yaqub Chaudhary , Jonnie Penn

The development of Large Language Models (LLMs) has notably transformed numerous sectors, offering impressive text generation capabilities. Yet, the reliability and truthfulness of these models remain pressing concerns. To this end, we…

计算与语言 · 计算机科学 2024-02-12 Satyapriya Krishna , Chirag Agarwal , Himabindu Lakkaraju

Large Language Models (LLMs) are increasingly being integrated into the scientific peer-review process, raising new questions about their reliability and resilience to manipulation. In this work, we investigate the potential for hidden…

密码学与安全 · 计算机科学 2026-03-31 Matteo Gioele Collu , Umberto Salviati , Roberto Confalonieri , Mauro Conti , Giovanni Apruzzese